Python is a great language for doing data analysis, primarily because of the fantastic ecosystem of data-centric python packages. Pandas is one of those packages and makes importing and analyzing data much easier.
Pandas Period.freq attribute returns the frequency applied on the given Period object.
Syntax : Period.freq
Parameters : None
Return : frequency
Example #1: Use Period.freq attribute to find the time series frequency applied on the given Period object.
# importing pandas as pd import pandas as pd   # Create the Period object prd = pd.Period(freq ='D', year = 2001, month = 2, day = 21)   # Print the Period object print(prd) |
Output :
Now we will use the Period.freq attribute to find the frequency applied on prd object.
# return the frequency prd.freq |
Output :
As we can see in the output, the Period.freq attribute has returned ‘Day’ indicating that the time series frequency applied on the given object was day.
Example #2: Use Period.freq attribute to find the time series frequency applied on the given Period object.
# importing pandas as pd import pandas as pd   # Create the Period object prd = pd.Period(freq ='Q', year = 2006, quarter = 1)   # Print the object print(prd) |
Output :
Now we will use the Period.freq attribute to find the frequency applied on prd object.
# return the frequency prd.freq |
Output :
As we can see in the output, the Period.freq attribute has returned ‘QuarterEnd’ indicating that the time series frequency applied on the given object was ‘Quarter’.
